[1]张凤静,周建江,夏伟杰.基于双目立体视觉的汽车安全车距测量方法[J].智能系统学报,2011,6(1):79-84.
ZHANG Fengjing,ZHOU Jianjiang,XIA Weijie.Research of vehicle security spacing measurements based on binocular stereovision[J].CAAI Transactions on Intelligent Systems,2011,6(1):79-84.
点击复制
ZHANG Fengjing,ZHOU Jianjiang,XIA Weijie.Research of vehicle security spacing measurements based on binocular stereovision[J].CAAI Transactions on Intelligent Systems,2011,6(1):79-84.
基于双目立体视觉的汽车安全车距测量方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
6
期数:
2011年第1期
页码:
79-84
栏目:
学术论文—机器感知与模式识别
出版日期:
2011-02-25
- Title:
- Research of vehicle security spacing measurements based on binocular stereovision
- 文章编号:
- 1673-4785(2011)01-0079-06
- Keywords:
- intelligent transportation; vehicle distance; binocular stereovision; common perpendicular midpoint
- 分类号:
- TP391
- 文献标志码:
- A
- 摘要:
- 汽车安全车距测量作为智能交通系统的一个重要分支是近年来的研究热点.本文阐述了双目立体视觉的原理，提出一种应用于高速公路上的安全车距测量方法.该方法根据目标车辆在左右摄像头所获的图像中对应的不同坐标，利用公垂线中点法计算出目标车辆到摄像头的距离.实验结果表明：该测距方法测量范围广，对远距离测量也适用；测量精度能满足智能交通中车辆安全距离测量的实际需要，是一种有效的前方车距测量方法.
- Abstract:
- As one of the research topics of intelligent transportation systems (ITS), systems for earlywarning against collision have drawn much attention in recent years. Based on the principle of binocular stereovision, a spacing measurement program for security vehicles on the expressway was proposed. According to the coordinates corresponding to two binocular images of the target vehicle obtained by the left and right cameras, the distance between the target vehicle and the camera could be calculated by employing the common perpendicular midpoint method. The results show that this measurement program can measure a wide range of distance and can also be applied to remote distances. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.
- 参考文献/References:
-
［1］雷克萨斯LS460四大安全新技术亮相日内瓦车展［EB/OL］. ［20100415］. http://www.autoelectronics.eetchina.com/ART_8800409099_2100003_NT_51853e97.HTM,20060306.
［2］富士重工展示“EyeSight”的立体摄像头及图像处理LSL［EB/OL］. ［20100415］. http://www.chinavision.net/news/sjyj/yw/200806/36419.html, 20080611.
［3］Bumblebee2［EB/OL］. ［20100415］. http://www.ptgrey.com/products/stereo.asp,2010.
?［4］顾柏园.基于单目视觉的安全车距预警系统［D］.长春：吉林大学交通学院, 2006: 1133.
GU Baiyuan. Study on the forward collision warning system based on monocular vision［D］. Changchun: College of Traffic, Jilin University, 2006: 1133.
［5］周欣,黄席樾,黎昱.基于单目视觉的高速公路车道保持与距离测量［J］.中国图象图形学报, 2003, 8(5): 590595.
ZHOU Xin, HUANG Xiyue, LI Yu. Lane keeping and distance measurement based on monocular vision［J］. Journal of Image and Graphics, 2003, 8(5): 590595.
［6］谢毅.基于DSP及机器视觉的道路识别与障碍物检测［D］.重庆：重庆大学自动化学院, 2009: 168.
XIE Yi. Lane and road detection based on DSP and machine vision［D］. Chongqing: College of Automation, Chongqing University, 2009: 168.
［7］周俊杰.基于单目视觉的夜间车辆和车距检测［D］.南京：南京理工大学计算机科学与技术学院, 2007: 156.
ZHOU Junjie. Vehicle and vehicle distance detection in the nighttime based on monocular vision［D］. Nanjing: Computer Science and Technology College, Nanjing University of Science and Technology, 2007: 156.
［8］马颂德，张正友.计算机视觉——计算理论与算法基础［M］.北京:科学出版社, 1998: 5294.
［9］ZHANG Zhengyou. A flexible new technique for camera calibration［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11): 13301334.
［10］刘晶晶.基于双目立体视觉的三维定位技术研究［D］.武汉：华中科技大学计算机科学与技术学院, 2007: 1534.
LIU Jingjing. Research on 3D positioning technique based on binocular stereo vision［D］.Wuhan: College of Computer Science and Technology, Huazhong University of Science and Technology, 2007: 1534.
［11］TRUCCO E, VERRI A. Introductory techniques for 3D computer vision［M］. Upper Saddle River, USA: Prentice Hall, 1998.
［12］张钧,张宏,刘小茂,等.双目立体视觉中物点定位的一种快速算法［J］.信息与控制, 2009, 38(5): 563570.
?ZHANG Jun, ZHANG Hong, LIU Xiaomao, et al. A fast algorithm for locating the object point in binocular stereovision［J］. Information and Control, 2009, 38(5): 563570.
［13］王虹,刘嵩鹤,刘著铭.基于双目立体视觉安全车辆间距测量技术研究［J］.交通与计算机, 2007, 25(6): 9093.
WANG Hong, LIU Songhe, LIU Zhuming. Binocular stereovisionbased security vehicles spacing survey technology［J］. Computer and Communications, 2007, 25(6): 9093.
- 相似文献/References:
-
[1]张立东,王英龙.公交优先模糊控制算法研究[J].智能系统学报,2007,2(3):59.
ZHANG Li-dong,WANG Ying-long.Study of a fuzzy control algorithm for public transit pri ority[J].CAAI Transactions on Intelligent Systems,2007,2():59.
[2]陈亮,何为,韩力群.RBF神经网络的行车路径代价函数建模[J].智能系统学报,2011,6(5):424.
CHEN Liang,HE Wei,HAN Liqun.Radial basis function neural network modeling of the traffic path cost function[J].CAAI Transactions on Intelligent Systems,2011,6():424.
[3]史晓鹏,何为,韩力群.采用Hough变换的道路边界检测算法[J].智能系统学报,2012,7(1):81.
SHI Xiaopeng,HE Wei,HAN Liqun.A road edge detection algorithm based on the Hough transform[J].CAAI Transactions on Intelligent Systems,2012,7():81.
[4]陈亮,何为,韩力群.城市交通最优路径算法[J].智能系统学报,2012,7(2):167.
CHEN Liang,HE Wei,HAN Liqun.Study on an urban transportation optimal path algorithm[J].CAAI Transactions on Intelligent Systems,2012,7():167.
[5]毕晓君,刘国安,肖婧.基于自适应差分进化的干线交通信号协调控制[J].智能系统学报,2012,7(5):437.
BI Xiaojun,LIU Guoan,XIAO Jing.Coordination and control of arterial traffic signalsbased on adaptive differential evolution[J].CAAI Transactions on Intelligent Systems,2012,7():437.
[6]李伯涵,郭茂祖,赵玲玲.基于分割注意力机制残差网络的城市区域客流量预测[J].智能系统学报,2022,17(4):839.[doi:10.11992/tis.202202014]
LI Bohan,GUO Maozu,ZHAO Lingling.Passenger flow prediction in urban areas based on residual networks with split attention mechanism[J].CAAI Transactions on Intelligent Systems,2022,17():839.[doi:10.11992/tis.202202014]
备注/Memo
收稿日期：2010-07-11.
基金项目：美国德州仪器大学计划创新基金资助项目；南京航空航天大学研究生创新基地资助项目（20090907）.
通信作者：张凤静.
?E-mail:zhfengjing1986@yahoo.com.cn.
作者简介：
张凤静，女，1986年生，硕士研究生，主要研究方向为计算机视觉、信号与信息处理.
周建江，男，1962年生，教授、博士生导师，主要研究方向为数字视频处理、雷达目标特性分析与特征控制、DSP应用.先后主持或参加国家“863”计划、国防基金、航空基金、国防预研、国防重点型号等科研项目40余项.曾获得省部级科技进步奖、教育部科技进步奖、国家级教学成果奖、省级教学成果特等奖，航空部二、三等功，光华基金三等奖.发表学术论文27篇，参编出版教材3部.
夏伟杰，男,1979年生，博士研究生、讲师，主要研究方向为图像信号处理、计算机视觉、DSP应用.
更新日期/Last Update:
2011-04-13